The processing of large volumes of data, also called big-data applications, has the aim of deriving new information or knowledge from mass data and to generate new business by this means. This processing of large volumes of data profits from a multiplicity of automatisms which are implemented in big-data systems. However, for this purpose, they must be restricted to the interfaces which are offered by the big-data systems. But the possibilities of these applications depend on the availability and accessibility of the basic data. The options of exploitation, optimization and marketing based on in-house data are often already largely exhausted. Either the data pool needed for big-data applications does not contain all data required so that the big-data applications cannot be implemented or only suboptimally, or the access to the required data is too complex, expensive, circumstantial and associated with individual negotiations between the companies involved or can often not be completed due to mistrust.